Students Learning Experiences and Psychological Pressure in Social Media Analytics

Authors

  • T. Ambikadevi Amma Professor & Principal, Department of Computer Science and Engineering, Nehru College of Engineering and Research Centre, Pampady, India
  • K. Arun Assistant Professor, Department of Computer Science and Engineering, Nehru College of Engineering and Research Centre, Pampady, India
  • K. M. Vipin Assistant Professor, Department of Computer Science and Engineering, Nehru College of Engineering and Research Centre, Pampady, India
  • A. B. Neethu PG Student, Department of Computer Science and Engineering, Nehru College of Engineering and Research Centre, Pampady, India

Keywords:

Learning experiences, Psychological pressure, Naive Bayes Multi label classifier

Abstract

The real time application mainly focuses on the sentiments and behavioural analysis which includes the social media. The main objective is to analyse the social media to extract sentiments that determine the learning experiences. The Microblogging services like twitter is used popular, where the create messages for all status is called tweets and post opinions about some events based on real time. The sentiment analysis is to classify positive, negative and neutral based on the tweets they posted in social media. The psychological pressure is predicts levels of stress depends on the tweets. The qualitative analysis is performed by the Naïve Bayes Multi label classifier and analyse word frequency counts using tweets. To analyse the students overall performance in the learning environments.

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Published

15-07-2020

How to Cite

[1]
T. A. Amma, K. Arun, K. M. . Vipin, and A. B. Neethu, “Students Learning Experiences and Psychological Pressure in Social Media Analytics”, IJRESM, vol. 3, no. 7, pp. 82–87, Jul. 2020.

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Articles